def readFromString(inputString, reactionDefinitions, useID, speciesEquivalence=None, atomize=False): ''' one of the library's main entry methods. Process data from a string ''' try: reader = libsbml.SBMLReader() document = reader.readSBMLFromString(inputString) parser = SBML2BNGL(document.getModel(), useID) bioGrid = False if bioGrid: loadBioGrid() database = structures.Databases() namingConventions = resource_path('config/namingConventions.json') if atomize: translator, onlySynDec = mc.transformMolecules( parser, database, reactionDefinitions, namingConventions, speciesEquivalence, bioGrid) else: translator = {} return analyzeHelper(document, reactionDefinitions, useID, '', speciesEquivalence, atomize, translator)[-2] except: return -5
def obtainSCT( self, fileName, reactionDefinitions, useID, namingConventions, speciesEquivalences=None, ): """ one of the library's main entry methods. Process data from a file to obtain the species composition table, a dictionary describing the chemical history of different elements in the system """ reader = libsbml.SBMLReader() document = reader.readSBMLFromFile(fileName) parser = SBML2BNGL(document.getModel(), useID) database = structures.Databases() database.forceModificationFlag = True database = mc.createSpeciesCompositionGraph( parser, database, reactionDefinitions, namingConventions, speciesEquivalences=speciesEquivalences, bioGridFlag=False, ) return database.prunnedDependencyGraph, database, document
def loadTranslator(fileName, jsonFile): reader = libsbml.SBMLReader() document = reader.readSBMLFromFile('XMLExamples/curated/BIOMD0000000' + fileName + '.xml') parser = libsbml2bngl.SBML2BNGL(document.getModel()) database = structures.Databases() translator = m2c.transformMolecules( parser, database, 'reactionDefinitions/reactionDefinition' + str(jsonFile) + '.json') return translator
def analyzeFile(bioNumber, reactionDefinitions, useID, namingConventions, outputFile, speciesEquivalence=None, atomize=False, bioGrid=False): ''' one of the library's main entry methods. Process data from a file ''' logMess.log = [] logMess.counter = -1 reader = libsbml.SBMLReader() document = reader.readSBMLFromFile(bioNumber) parser = SBML2BNGL(document.getModel(), useID) database = structures.Databases() database.forceModificationFlag = True bioGridDict = {} if bioGrid: bioGridDict = loadBioGrid() #call the atomizer (or not). structured molecules are contained in translator #onlysyndec is a boolean saying if a model is just synthesis of decay reactions if atomize: translator, onlySynDec = mc.transformMolecules(parser, database, reactionDefinitions, namingConventions, speciesEquivalence, bioGrid) else: translator = {} #process other sections of the sbml file (functions reactions etc.) returnArray = analyzeHelper(document, reactionDefinitions, useID, outputFile, speciesEquivalence, atomize, translator) with open(outputFile, 'w') as f: f.write(returnArray[-2]) #with open('{0}.dict'.format(outputFile),'wb') as f: # pickle.dump(returnArray[-1],f) if atomize and onlySynDec: returnArray = list(returnArray) returnArray[0] = -1 return tuple(returnArray[0:-2])
def obtainSCT(fileName, reactionDefinitions, useID, namingConventions): ''' one of the library's main entry methods. Process data from a file ''' logMess.log = [] logMess.counter = -1 reader = libsbml.SBMLReader() document = reader.readSBMLFromFile(fileName) parser = SBML2BNGL(document.getModel(), useID) database = structures.Databases() database.forceModificationFlag = True sct, database = mc.createSpeciesCompositionGraph(parser, database, reactionDefinitions, namingConventions, speciesEquivalences=None, bioGridFlag=False) return sct, database, document
def extractCompartmentStatistics(bioNumber, useID, reactionDefinitions, speciesEquivalence): ''' Iterate over the translated species and check which compartments are used together, and how. ''' reader = libsbml.SBMLReader() document = reader.readSBMLFromFile(bioNumber) parser = SBML2BNGL(document.getModel(), useID) database = structures.Databases() #call the atomizer (or not) #if atomize: translator, onlySynDec = mc.transformMolecules(parser, database, reactionDefinitions, speciesEquivalence) #else: # translator={} compartmentPairs = {} for element in translator: temp = extractCompartmentCoIncidence(translator[element]) for element in temp: if element not in compartmentPairs: compartmentPairs[element] = temp[element] else: compartmentPairs[element].update(temp[element]) finalCompartmentPairs = {} print '-----' for element in compartmentPairs: if element[0][0] not in finalCompartmentPairs: finalCompartmentPairs[element[0][0]] = {} finalCompartmentPairs[element[0][0]][tuple( [element[0][1], element[1][1]])] = compartmentPairs[element] return finalCompartmentPairs
def analyzeHelper(document, reactionDefinitions, useID, outputFile, speciesEquivalence, atomize, translator, bioGrid=False): ''' taking the atomized dictionary and a series of data structure, this method does the actual string output. ''' useArtificialRules = False parser = SBML2BNGL(document.getModel(), useID) database = structures.Databases() #translator,log,rdf = m2c.transformMolecules(parser,database,reactionDefinitions,speciesEquivalence) #try: #bioGridDict = {} #if biogrid: # bioGridDict = biogrid() #if atomize: # translator = mc.transformMolecules(parser,database,reactionDefinitions,speciesEquivalence,bioGridDict) #else: # translator={} parser = SBML2BNGL(document.getModel(), useID) #except: # print 'failure' # return None,None,None,None #translator = {} param, zparam = parser.getParameters() molecules, initialConditions, observables, speciesDict = parser.getSpecies( translator, [x.split(' ')[0] for x in param]) #finally, adjust parameters and initial concentrations according to whatever initialassignments say param, zparam, initialConditions = parser.getInitialAssignments( translator, param, zparam, molecules, initialConditions) compartments = parser.getCompartments() functions = [] assigmentRuleDefinedParameters = [] reactionParameters, rules, rateFunctions = parser.getReactions( translator, len(compartments) > 1, atomize=atomize) functions.extend(rateFunctions) aParameters, aRules, nonzparam, artificialRules, removeParams, artificialObservables = parser.getAssignmentRules( zparam, param, molecules) for element in nonzparam: param.append('{0} 0'.format(element)) param = [x for x in param if x not in removeParams] tags = '@{0}'.format( compartments[0].split(' ')[0]) if len(compartments) == 1 else '@cell' molecules.extend([x.split(' ')[0] for x in removeParams]) if len(molecules) == 0: compartments = [] observables.extend('Species {0} {0}'.format(x.split(' ')[0]) for x in removeParams) for x in removeParams: initialConditions.append( x.split(' ')[0] + tags + ' ' + x.split(' ')[1]) ##Comment out those parameters that are defined with assignment rules ##TODO: I think this is correct, but it may need to be checked tmpParams = [] for idx, parameter in enumerate(param): for key in artificialObservables: if re.search('^{0}\s'.format(key), parameter) != None: assigmentRuleDefinedParameters.append(idx) tmpParams.extend(artificialObservables) tmpParams.extend(removeParams) tmpParams = set(tmpParams) correctRulesWithParenthesis(rules, tmpParams) for element in assigmentRuleDefinedParameters: param[element] = '#' + param[element] deleteMolecules = [] deleteMoleculesFlag = True for key in artificialObservables: flag = -1 for idx, observable in enumerate(observables): if 'Species {0} {0}()'.format(key) in observable: flag = idx if flag != -1: observables.pop(flag) functions.append(artificialObservables[key]) flag = -1 if '{0}()'.format(key) in molecules: flag = molecules.index('{0}()'.format(key)) if flag != -1: if deleteMoleculesFlag: deleteMolecules.append(flag) else: deleteMolecules.append(key) #result =validateReactionUsage(molecules[flag],rules) #if result != None: # logMess('ERROR','Pseudo observable {0} in reaction {1}'.format(molecules[flag],result)) #molecules.pop(flag) flag = -1 for idx, specie in enumerate(initialConditions): if ':{0}('.format(key) in specie: flag = idx if flag != -1: initialConditions[flag] = '#' + initialConditions[flag] for flag in sorted(deleteMolecules, reverse=True): if deleteMoleculesFlag: logMess( 'WARNING:Simulation', '{0} reported as function, but usage is ambiguous'.format( molecules[flag])) result = validateReactionUsage(molecules[flag], rules) if result != None: logMess( 'ERROR:Simulation', 'Pseudo observable {0} in reaction {1}'.format( molecules[flag], result)) molecules.pop(flag) else: logMess( 'WARNING:Simulation', '{0} reported as species, but usage is ambiguous.'.format( flag)) artificialObservables.pop(flag) functions.extend(aRules) sbmlfunctions = parser.getSBMLFunctions() processFunctions(functions, sbmlfunctions, artificialObservables, rateFunctions) for interation in range(0, 3): for sbml2 in sbmlfunctions: for sbml in sbmlfunctions: if sbml == sbml2: continue if sbml in sbmlfunctions[sbml2]: sbmlfunctions[sbml2] = writer.extendFunction( sbmlfunctions[sbml2], sbml, sbmlfunctions[sbml]) functions = reorderFunctions(functions) functions = changeNames(functions, aParameters) # print [x for x in functions if 'functionRate60' in x] functions = unrollFunctions(functions) rules = changeRates(rules, aParameters) if len(compartments) > 1 and 'cell 3 1.0' not in compartments: compartments.append('cell 3 1.0') #sbml always has the 'cell' default compartment, even when it #doesn't declare it elif len(compartments) == 0 and len(molecules) != 0: compartments.append('cell 3 1.0') if len(artificialRules) + len(rules) == 0: logMess('ERROR:Simulation', 'The file contains no reactions') if useArtificialRules or len(rules) == 0: rules = ['#{0}'.format(x) for x in rules] evaluate = evaluation(len(observables), translator) artificialRules.extend(rules) rules = artificialRules else: artificialRules = ['#{0}'.format(x) for x in artificialRules] evaluate = evaluation(len(observables), translator) rules.extend(artificialRules) commentDictionary = {} if atomize: commentDictionary[ 'notes'] = "'This is an atomized translation of an SBML model created on {0}.".format( time.strftime("%d/%m/%Y")) else: commentDictionary[ 'notes'] = "'This is a plain translation of an SBML model created on {0}.".format( time.strftime("%d/%m/%Y")) commentDictionary[ 'notes'] += " The original model has {0} molecules and {1} reactions. The translated model has {2} molecules and {3} rules'".format( parser.model.getNumSpecies(), parser.model.getNumReactions(), len(molecules), len(set(rules))) meta = parser.getMetaInformation(commentDictionary) from collections import OrderedDict finalString = writer.finalText(meta, param + reactionParameters, molecules, initialConditions, list(OrderedDict.fromkeys(observables)), list(OrderedDict.fromkeys(rules)), functions, compartments, outputFile) #print outputFile logMess( 'INFO:Summary', 'File contains {0} molecules out of {1} original SBML species'.format( len(molecules), len(observables))) #store a logfile try: if len(logMess.log) > 0: with open(outputFile + '.log', 'w') as f: for element in logMess.log: f.write(element + '\n') except AttributeError: print "error" except IOError: pass #print "" #rate of each classified rule evaluate2 = 0 if len( observables) == 0 else len(molecules) * 1.0 / len(observables) return len(rules), len(observables), evaluate, evaluate2, len( compartments), parser.getSpeciesAnnotation(), finalString, speciesDict '''